Studies on the Acculturation of Young Refugees in the Educational Domain: A Scoping Review of Research and Methods
Bibliographic record
Abstract
Abstract Given that children and adolescents constitute a growing and significant share of forced migrants worldwide, assessing the state of research on and the methods used to study the acculturation of this group is both timely and essential. The acculturation of refugee children and adolescents in host countries occurs primarily within educational institutions and through the acquisition of the language of the new host society. This scoping review of peer-reviewed journal articles published between 1987 and 2016 (N = 192 eligible studies) examined the extent to which individual-level factors (e.g., gender, age) and contextual factors (e.g., country of residence) emphasized by acculturation models have been considered in research involving young refugees in the educational domain. In addition, the research designs and methods applied in these studies were evaluated, and content analysis was performed to examine whether individual-level factors considered in the sample of studies were related to educational outcomes of young refugees. Overall, the review revealed that very few studies provided adequate information on sample composition, or considered individual and contextual factors, thus leaving crucial gaps in the knowledge about the acculturation of young refugees. Guidelines for future research are proposed to remedy the identified research deficits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".